-We present a scalable Dynamic Power Management (DPM) schem e where malleable applications may change their
degree of parallelism at run time depending upon the workload and performance constraints. We employ a per-application predictive
power manager that autonomously controls the power states of the cores with the goal of energy efﬁciency. Furthermore, our DPM
allows the applications to lend their idle cores for a short time period to expedite other critical applications. In this way, it allows for
application-level scalability, while aiming at the overall system energy optimization. Compared to state-of-the-art centralized and
distributed power management approaches, we achieve up to 58 percent (average %15-20 percent) ED2P reduction.

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